1. Field
This invention generally relates to methods for determining wettability of fluids in a reservoir using nuclear magnetic resonance data (NMR).
2. Background
Wettability is a critical issue in many carbonate reservoirs. Such reservoirs often show significant variability in wettability, even within one formation. The term wettability can be understood as the tendency of a fluid to spread on and preferentially adhere to or “wet” a solid surface in the presence of other immiscible fluids. Knowledge of the wettability of an oil reservoir is important to reservoir and production engineers because reservoir wettability influences reservoir properties such as residual oil saturation, relative permeability and capillary pressure. See F. G. Craig in the Society of Professional Engineers (SPE) Monograph on “The Reservoir Engineering Aspects of Waterflooding,” 1971. Thus, reservoir wettability information is crucial for efficient oil recovery. This information is becoming increasingly important as secondary and tertiary recovery methods are used to recover remaining reserves in old producing fields. For example, in a water-wet reservoir, a waterflood can be an efficient method of recovering remaining reserves after primary production, whereas, in a mixed-wet reservoir, a surfactant flood would be more effective in recovering the remaining oil.
A Standard Laboratory Wettability Measurement
The flow rate of oil through a rock under a pressure gradient is described by the product of permeability, k and relative permeability, kr. Permeability is a geometrical quantity and is determined by the geometry of the pore space. The relative permeability, on the other hand, is controlled by the configuration of the fluid phase within the pore space. Wettability strongly affects this configuration.
For this reason, wettability of a crude oil/brine/rock system is of central importance in determining the efficiency of oil recovery by water displacement in oil reservoirs. According to W. Looyestijn and J. Hofman (W. Looyestijn and J. Hofman, Titled “Wettability-index determination by nuclear magnetic resonance,” SPE, Reservoir Evaluation and Engineering, April 2006: p. 146-153) (hereafter “Looyestijn 2006”), in many Middle Eastern carbonate fields, wettability is rated as one of the critical uncertainties.
Measuring wettability is time consuming and notoriously difficult to measure reliably. In the laboratory, wettability is usually characterized by the Amott index (E. Amott, titled “Observations relating to the wettability of porous rock,” Trans. AIME, 216: p. 156-162, (1959)), or the USBM index (E. C. Donaldson, R. D. Thomas, and P. B. Lorenz, titled “Wettability determination and its effect on recovery efficiency,” SPEJ, March 1969: p. 13-20). The core samples are first brought to the desired saturation and then the downhole wettability is attempted to be restored by aging the sample at an elevated temperature for typically four weeks. The resulting wettability index gives an average value for the core. However, it is well known that the wettability in a reservoir is likely to vary spatially and with production. In addition, Robin et al. (M. Robin, E. Rosenberg, and O. Fassi-Fihri, titled “Wettability studies at the pore level: A new approach by use of Cryo-SEM,” SPE Formation Evaluation, March 1995: p. 11-19) measured the fluid configuration in rocks at the micron level using cryo-SEM and reported heterogeneity of wettability at the pore level.
However, this implies that an average wettability index can be misleading to predict the fluid configuration inside the core. Clearly, a direct measurement of the fluid configuration downhole will circumvent many of the present difficulties.
At least one widely-used wettability indicator is the use of contact angles in water-oil-solid systems. In addition, other laboratory tests for wettability are also available, including imbibition measurements. However, these are laboratory measurements and cannot be performed downhole. In contrast, a nuclear magnetic resonance (NMR) approach can provide a qualitative wettability indicator and has the advantage of being able to assess the fluids and rock at reservoir conditions.
NMR measurements on fluid saturated rocks are sensitive to the wettability of the rock matrix because relaxation rates of fluid molecules are enhanced when they are in contact with rock surfaces. This is because rock surfaces often have paramagnetic ions or magnetic ions which can provide efficient relaxation for the fluid molecules. Reservoir wettability not only depends on the inherent property of the rock matrix, but also on surface interactions between the rock matrix and the fluid molecules, i.e., it also depends on the attractive forces that exist between the polar oil molecules and those on rock matrix surfaces.
Many laboratory NMR wettability studies have been reported in the literature. The first NMR study on wettability was by Brown and Fatt, who made T1 relaxation measurements on water-saturated unconsolidated sand packs constructed with different fractions of water-wet and oil-wet sand grains. See R. J. S. Brown and I. Fatt, “Measurements of Fractional Wettability of Oilfield Rocks by the Nuclear Magnetic Relaxation Method,” Petroleum Transactions, AIME, 207, pp. 262-264, 1956. Numerous studies on the application of NMR to wettability have been published since then. See Q. Zhang, C. C. Huang, and G. J. Hirasaki, “Interpretation of Wettability in Sandstones with NMR Analysis,” Petrophysics, May-June, 2000, Vol. 41, No. 3, pp. 223-233.
Prior NMR studies of wettability of partially saturated reservoir rocks have been mostly limited to rocks saturated with brine and low viscosity hydrocarbons, such as Soltrol, decane and dodecane. These low viscosity fluids are characterized as having narrow T1 and T2 distributions and long relaxation times. Accordingly, it is relatively simple to distinguish the hydrocarbon signal from the brine signal in the relaxation time distributions of partially saturated rocks. The oil relaxation times in the rocks can then be compared with those of the bulk hydrocarbon (i.e., outside the rock) to infer whether the oil is wetting the surface. However, wettability inferred from experiments using refined or pure hydrocarbons is not indicative of the wettability of the same rocks saturated with crude oil, because crude oils may contain asphaltenes and resins, which are known to have surface-active polar molecules that are attracted to opposite charge sites on the pore surfaces.
The above described approaches to the determination of rock wettability use laboratory measurements. Reservoir wettability determination from laboratory measurements is not definitive because it is not possible to accurately mimic reservoir conditions in the laboratory, as noted above. In fact, the very processes required to obtain laboratory samples can alter the reservoir wettability. See N. R. Morrow, “Wettability and Its Effect on Oil Recovery,” in the J. of Pet. Tech., December, 1990, pp. 1476 1484.
As discussed above, both water and hydrocarbons in earth formations produce detectable NMR signals. Thus, it is desirable for at least one method for determining wettability that the signals from water and hydrocarbons be separable so that hydrocarbon-bearing zones may be identified. However, it is not always easy to distinguish which signals are from water and which are from hydrocarbons. Various methods have been proposed to separately identify water and hydrocarbon signals.
Known Methods for Separately Identifying Water and Hydrocarbon Signals
The differential spectrum (DSM) and shifted spectrum (SSM) methods proposed by Akkurt et al. in “NMR Logging of Natural Gas Reservoirs,” Paper N. Transactions of the Society of Professional Well Log Analysts (SPWLA) Annual Logging Symposium, 1995, compare T2 distributions derived from two Carr-Purcell-Meiboom-Gill (CPMG) measurements performed with different polarization times (DSM) or echo-spacings (SSM). A modification to these methods, known as time domain analysis (TDA), was later introduced by Prammer et al. in “Lithology-Independent Gas Detection by Gradient-NMR Logging,” SPE paper 30562, 1995. In TDA, “difference” data are computed directly in the time domain by subtracting one set of the measured amplitudes from the other.” The difference dataset is then assumed to contain only light oil and/or gas. In TDA, relative contributions from light oil or gas are derived by performing a linear least squares analysis of the difference data using assumed NMR responses for these fluids. Both DSM and TDA assume that the water signal has substantially shorter T1 relaxation times than those of the hydrocarbons. This assumption is not always valid, however. Most notably, this assumption fails in formations where there are large pores or where the hydrocarbon is of intermediate or high viscosity. The SSM method and its successor, the enhanced diffusion method (EDM) proposed by Akkurt et al. in “Enhanced Diffusion: Expanding the Range of NMR Direct Hydrocarbon Typing Applications,” Paper GG. Transactions of the Society of Professional Well Log Analysts (SPWLA) Annual Logging Symposium, 1998, separate gas, oil and water contributions based on changes in the T2 distributions that result from changes in the echo spacing of CPMG measurements. The methods are applicable in a limited range of circumstances and the accuracy of the result is significantly compromised by incomplete separation of water and hydrocarbon signals in the T2 domain. Moreover, these methods are designed to function with CPMG sequences. However, with the diffusion-based methods, CPMG pulse sequences provide poor signal to noise ratios due to the reduced number of echoes that can be measured. A strategy for combining and selecting these different NMR methods has been described recently by Coates et al. in U.S. Pat. No. 6,366,087.
The diffusion-editing (DE) pulse sequence by Hurlimann et al. provides a different approach. See M. D. Hurlimann et al., “Diffusion-Editing: New NMR Measurement of Saturation and Pore Geometry,” paper presented at the 2002 Annual Meeting of the Society of Professional Well Log Analysts, Osio, Japan, Jun. 2 5; see also, U.S. Pat. No. 6,570,382, filed on Nov. 28, 2000, by Hurlimann. This patent is assigned to the same assignee as the present invention and is hereby incorporated by reference. DE pulse sequences are similar to the CPMG sequences except that the initial two echoes are acquired with longer echo spacings and the third and subsequent echoes are acquired with shorter echo spacings. In DE pulse sequences, diffusion information is encoded during the acquisition of the first two echoes, whereas the third and subsequent echoes provide bulk and surface relaxation time information with relatively little attenuation of the signal by diffusion. Using a conventional CPMG sequence to encode the diffusion information requires a long inter-echo spacing, which results in poor bulk and surface relaxation time information because diffusion decay attenuates the signal after relatively few echoes. Consequently, a suite of data acquired with DE sequences provides better diffusion information and signal-to-noise ratio in the spin-echo data, as compared to an analogous suite acquired with CPMG sequences. Therefore, DE sequences can provide more accurate and robust computations of brine and oil T2 distributions than CPMG sequences.
In addition to DE sequences, specialized interpretation methods have been developed for NMR data in order to further enhance hydrocarbon detection. These methods typically apply forward modeling to suites of NMR data acquired with different parameters. The suite of NMR data are typically acquired with different echo spacings (TE) or polarization times (WT), and sometimes acquired with different magnetic field gradients (G). DE sequences are one example of such data acquisition. Two exemplary methods include: the MACNMR proposed by Slijkerman et al., SPE paper 56768, “Processing of Multi-Acquisition NMR Data,” 1999, and the Magnetic Resonance Fluid characterization (MRF) method disclosed in U.S. Pat. No. 6,229,308 B1 issued to Freedman and assigned to the assignee of the present invention (“the Freedman patent”). The Freedman patent is hereby incorporated by reference.
The Magnetic Resonance Fluid characterization (MRF) method is capable of obtaining separate oil and water T2 distributions. This method uses a Constituent Viscosity Model (CVM), which relates relaxation time and diffusion rates to constituent viscosities whose geometric mean is identical to the macroscopic fluid viscosity. With the MRF method, estimates for water and hydrocarbon volumes are obtained by applying a forward model to simulate the NMR responses to a suite of NMR measurements acquired with different parameters. Specifically, The MRF technique is based on established physical laws which are calibrated empirically to account for the downhole fluid NMR responses. By using realistic fluid models, MRF aims to minimize the number of adjustable parameters to be compatible with the information content of typical NMR log data. Since the model parameters are by design related to the individual fluid volumes and properties, determination of the parameter values (i.e., data-fitting) leads directly to estimates for petro-physical quantities of interest.
The forward-model approach relies on the validity of the fluid models employed. In “non-ideal” situations where fluid NMR responses deviate from the model behavior (oil-wet rocks, restricted diffusion), these techniques may lead to erroneous answers. In some circumstances, “non-ideal” responses may be identified by poor fit-quality, in which case the fluid models can be adjusted by modifying the appropriate model parameter. However, it may not be obvious which element of the fluid model should be modified and what modification is needed.
While the above mentioned prior art methods are useful in predicting the presence of hydrocarbons in the formations, it is desirable to have new methods that can utilized the gathered data such as electrical conductivity data, NMR data and/or in combination with other saturation and porosity measurements (e.g., resistivity, neutron and gamma rays), so as to determine fluid configurations and wettability properties in the formations.
Therefore, there is a need for methods that can determine reservoir wettability either under downhole conditions or on the surface, by non-limiting example, so as to provide for efficient oil recovery.